Polygons#

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import hvplot.pandas  # noqa

Using hvplot with geopandas is as simple as loading a geopandas dataframe and calling hvplot on it with geo=True.

import geopandas as gpd

countries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
countries.sample(5)
pop_est continent name iso_a3 gdp_md_est geometry
20 3398.0 South America Falkland Is. FLK 282 POLYGON ((-61.20000 -51.85000, -60.00000 -51.2...
73 1148130.0 Africa eSwatini SWZ 4471 POLYGON ((32.07167 -26.73382, 31.86806 -27.177...
102 216565318.0 Asia Pakistan PAK 278221 POLYGON ((77.83745 35.49401, 76.87172 34.65354...
142 5818553.0 Europe Denmark DNK 350104 MULTIPOLYGON (((9.92191 54.98310, 9.28205 54.8...
0 889953.0 Oceania Fiji FJI 5496 MULTIPOLYGON (((180.00000 -16.06713, 180.00000...
countries.hvplot(geo=True)

Control the color of the elements using the c option.

countries.hvplot.polygons(geo=True, c='pop_est', hover_cols='all')

You can even color by another series, such as population density:

countries.hvplot.polygons(geo=True, c=countries.pop_est/countries.area, clabel='pop density')
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Download this notebook from GitHub (right-click to download).